Thesis in M.E.
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Item An Integrated Approach for Supply chain Optimization Using Machine Learning Techniques(Chittagong University of Engineering and Technology, 2-Sep-2024) Faisal, S.M.FahimIn the modern world, supply chains completely rely on data to function properly underItem AN INTEGRATED APPROACH FOR SUPPLY CHAIN OPTIMIZATION USING MACHINE LEARNING TECHNIQUES(CUET, 2-Sep-2024) Faisal, S. M. FahimIn the modern world, supply chains completely rely on data to function properly under risk and uncertainty. Supply chain risk optimization is a process that involves identifying, assessing, and managing potential risks within a supply chain network to minimize disruptions. A machine learning analytics model of supply chain risk optimization uses data analytics and machine learning algorithms to understand and assess supply chain risks. Out of many types of risks involved in the supply chain, late delivery risk is the most common, and a lot of attention has been paid by researchers in this regard. The work presented in this thesis utilizes the DataCo Supply Chain dataset. Out of many risks, late delivery and fraud detection are considered in this research work to optimize the risks associated with the supply chain. In total, 15 different machine learning classification algorithms along with two hybrid algorithms are implemented and compared. The better performing hybridized classification algorithm is created in this paper combining the Multi-Layer Perceptron Classifier, Random Forest, and Extra Trees Classifier is put to the test. The hybrid algorithm outperforms all the algorithms and shows an accuracy of 99.45% and 99.15% for late delivery status prediction and fraud detection respectively. In the later part of the thesis, Deep Reinforcement Learning algorithms have been implemented for supply chain pricing policy optimization. The unique factor is that real-time data from an online marketplace in Bangladesh is used in this regard. Deep Q Network and State-Action-Reward-State-Action algorithm have been used, performance-wise Deep Q Network algorithm performed better and it achieved 19% more profit than constant price optimization. The overall work done in this thesis provides a solid foundation of integrated supply chain optimization by which supply chain managers can act proactively and can get benefit.Item Analytical and Experimental Analysis of Wheel Alignment System for Light Vehicle(CUET, 26-Sep-2023) Das, Riton KumerWheel alignment is an important factor that influences the performance of automotive vehicles. This study experimentally investigated the effects of wheel alignment, especially front wheel toe angle, tire pressure, vehicle load, and brake application, on fuel consumption and tire travel life for two different models of light vehicles. According to the analysis, the vehicle's wheel started to become out of alignment when its travel distance increased over time. It is observed that vehicle wheels became out of alignment due to changes in different factors, including vehicle load, road condition, brake application, tire pressure, suspension condition, etc. The experimental findings also demonstrate that a number of variables, including engine rpm, rolling resistance, energy consumption, fuel consumption, and tire wear of the vehicles, are strongly correlated with front wheel toe angles, tire pressure, vehicle load, and brake application. The test result shows that the increase in rolling resistance and energy consumption led to an increase in fuel consumption, tire wear rates, and travel costs. It is found that due to the misalignment of the front wheel toe angle, the car travels about 4.77 km (for left toe-in, 2.53°), 5.12 km (for left toe-out, -2.53°), 7.37 km (for total toe-in, 5.06°), and 7.63 km (for total toe-out, -5.06°) less for the same amount of fuel, and the KPL reduction rate is up to 38.22%, 42.24%, 73.99%, and 79.31%, respectively. In comparison to the front wheel's left toe-in angle, the fuel consumption rate is 4.02% higher at the front wheel's left toe-out angle. Additionally, it is found that when both wheels are at a toe angle, fuel consumption is a little bit higher. In the second experiment, the effect of tire inflation pressure on the fuel performance of a light vehicle at a front wheel total toe angle of 0.00°, 1.44° (toe-in), and -1.44° (toe-out) is investigated. The experimental finding shows that when tire pressure changes from over-inflated to under-inflated while maintaining a constant front wheel toe angle, the vehicle's engine rpm, rolling resistance, energy consumption, fuel consumption, and travel cost rates increase. In comparison to a total toe angle of 0.00°, a front wheel total toe-in angle of 1.44° results in a 3.62% increase in fuel consumption, while a front wheel total toe-out angle of -1.44° results in a 4.63% increase. In the third experiment, a Toyota Echo Plus-2ZZ-GE-02 light-duty vehicle is used to investigate the effect of vehicle load on fuel performance. It is revealed that when the vehicle load rose from low to high whileItem Ergonomic analysis of seats of human powered vehicles by digital human modeling for better ride comfort(CUET, 5-Mar-2024) Hai, Tasmia BinteRickshaws are essential for affordable and accessible transportation, particularly in densely populated urban areas. It is important to ensure the comfort of the rickshaw driver as it directly affects their health, well-being, and job satisfaction. It also influences customer satisfaction and safety. This study focuses on modifying the rickshaw driver's seat to enhance comfort while ensuring ergonomic principles are met. As proper cushioning, support, vibration absorption, and adjustability are key factors, this study involves measurements of rickshaw frames, CAD design of seat structures, ergonomic analysis using CATIA V5, and experimental vibration analysis.Item Experimental Investigation of Cycling Characteristics of Anatase TiO2 Nanotubes as Negative Electrode of Lithium-ion Batteries(CUET, 4-Oct-2023) Das, SimulLithium-ion batteries (LIBs) have emerged as a ground-breaking technology thatItem Fabrication and characterization of nature fiber based Self-healing composite materials.(CUET, 9-Jun-2024) Adil, Md. MahmudulRecent research has focused on microcapsule-based self-healing polymer composites, offering significant potential for repairing damaged polymeric materials. In this study, microcapsule-based jute fiber-reinforced epoxy self-healing composites were manufactured using the vacuum bagging technique. Epoxy was combined with 3 wt.% of water-insoluble and water-soluble epoxy microcapsules that were synthesized by the in-situ polymerization method. The resulting composite underwent assessment for healing efficiency via impact strength recovery. Incorporating microcapsules within the cracked surface of the composite facilitated healing, demonstrating notable improvements in efficiency. Results indicated that the epoxy composite healed from a 1 mm deep crack exhibited higher impact strength recovery than samples healed from a 1.5 mm deep crack, with healing efficiencies of 83.9% and 78.89%, respectively. Scanning electron microscopic (SEM) analysis showed that the microcapsule size varies from 1.45 μm to 1.83 μm. FTIR spectra confirmed the presence of relevant chemical groups in both microcapsules and the composite.Item REGAINING OF TRIBOLOGICAL BEHAVIOR OF USED LUBRICANT(CUET, 5-Nov-2023) Das, BiswajitThis research Project deals with the experimental analysis of regaining of tribological behavior of used Lubricant, for proper use of lubricants is very important. It has impact to the lifetime of machineries & friction of moving parts. And also improve of machine performance and increase smooth rotation of moving parts.Item Study on the Effect of Process Parameters of Laser Powder Bed Fusion on the Microstructure and Mechanical Properties of SAF 2507 Super Duplex Stainless Steel(University of Agder, Norway, 14-Aug-2024) SUVA, ANISUL ISLAMLaser-powder bed fusion (L-PBF) is a type of additive manufacturing (AM) that involves the addition of metal powders in a sequential layer-by-layer manner to create near-net-shape components. An outstanding characteristic of this technology is its ability to achieve high cooling rates, reaching up to 107 K/s. This unique characteristic has benefits in the production of high-strength stainless steel alloys, as it helps to reduce unwanted phase formation. SAF 2507 super duplex stainless steel (SAF 2507 SDSS), a type of stainless-steel alloy, contains around 25% chromium and 7% nickel, has a unique phase composition with an equal distribution of about 50% ferrite and 50% austenite and characterized by its higher mechanical strength and resistance to corrosion, which are attributed to its high levels of chromium and nickel content along with its low level of carbon. Producing intricate geometry with SAF 2507 using traditional methods with a specific phase composition is challenging and requires post-processing. LPBF is an alternative technology capable of manufacturing near-net-shape components with complicated geometry. It is important to conduct a comprehensive investigation to retain the desired phase composition while fabricating components using L-PBF. Although several studies have investigated the microstructure and mechanical properties of SAF 2507 using L-PBF. However, the influence of different L-PBF process parameters as well as energy density on microstructure and mechanical properties has yet to be investigated. This study examines the influence of L-PBF process parameters (laser power, scan speed, hatch distance) on the microstructure and mechanical properties of SAF 2507 SDSS. Additionally, the corrosion properties are investigated using the established optimum parameters. A design of experiment (DoE) was performed using the central composite design over a wide range of process parameters: laser power (100–300 W), scan speed (250–1000 mm/s), and hatch distance (50–180 μm) to investigate their effect on the microstructural and mechanical properties of SAF 2507. By implementing the selected parameter set, the as-built SAF 2507 SDSS sample had porosity less than 1%, a Vicker hardness ranging from 288 to 357 HV, a yield strength of 824 to 1220 MPa, an ultimate tensile strength of 965 to 1304 MPa, elongation of 6% to 18.1%, and a corrosion rate of 127.65 μm/y was determined. The findings derived from this investigation have the potential to facilitate the customization of component quality by meeting design specifications and minimizing as-built defects, thereby decreasing the need for post-processing.Item Synthesis and Electrochemical Cycling of Nanostructured Ti2C Mxene as Anode Materials for Lithium-ion Batteries(CUET, 18-Aug-2024) Chy, Mohammad Nezam UddinBy offering a high energy density, long cycle life, and relatively low self-discharge rates, LIBs have become the preferred choice for powering everything from smartphones to electric vehicles. Their ability to be rapidly charged and discharged while maintaining a compact and lightweight form has also made them essential in renewable energy systems, where they facilitate the storage of solar and wind energy. The electrochemical performance of a LIB greatly depends upon the anode material. The essential requirements for excellent anode material of Lithium-ion batteries (LIBs) are high safety, minimal volume expansion during the lithiation/de-lithiation process, high cyclic stability, and high Li+ storage capability. However, most of the anode materials for LIBs, such as graphite, SnO2, Si, Al, Li4Ti5O12, etc., have at least one issue. Hence, creating novel anode materials continues to be difficult. Broad adoption has already been started of MXenes materials in various energy storage technologies such as super-capacitors and batteries due to the increasing versatility of the preparation methods as well as the ongoing discovery of new members. Few MXenes have been investigated experimentally as anode of LIBs till date due to their distinct active voltage windows, large power capabilities, and longer cyclic life. Here, Ti2C MXene was synthesized by using an efficient NaOH etching technique. The surface appearance, structural composition, and crystalline structure were assessed using X-ray diffraction, SEM, and EDX analysis. The as-synthesized MXene were used as negative electrode in LIB and electrochemical performance were evaluated. First cycle charge-discharge capacities are found 658.02 mAhg-1 and 419.11 mAhg-1 respectively with an initial columbic efficiency of 63.6% and excellent capacity retention of 259.1 mAhg-1 is obtained after 100 cycles at a current density of 50 mAg-1. The excellent cyclic performance and stability of this cell are attributed to the unique properties of MXene structure such as high electronic conductivity, low operating voltage, large surface area and fast Li ion diffusion characteristicsItem Thermal Performance Analysis of the 3-φ Distribution Transformer Radiator with and without Fin Arrangement(CUET, Dec-2020) Ahmad, FaridTransformer plays a significant role in providing a reliable and useful electricity